aparico
commented
3 years ago I have also tried doing it locally.
Here are the results:
ROI initialized on [(144, 453), (1381, 440)]
Traceback (most recent call last):
File "C:\Python37\lib\site-packages\tensorflow_core\python\framework\importer.py", line 497, in _import_graph_def_internal
graph._c_graph, serialized, options) # pylint: disable=protected-access
tensorflow.python.framework.errors_impl.InvalidArgumentError: NodeDef mentions attr 'exponential_avg_factor' not in Op<name=FusedBatchNormV3; signature=x:T, scale:U, offset:U, mean:U, variance:U -> y:T, batch_mean:U, batch_variance:U, reserve_space_1:U, reserve_space_2:U, reserve_space_3:U; attr=T:type,allowed=[DT_HALF, DT_BFLOAT16, DT_FLOAT]; attr=U:type,allowed=[DT_FLOAT]; attr=epsilon:float,default=0.0001; attr=data_format:string,default="NHWC",allowed=["NHWC", "NCHW"]; attr=is_training:bool,default=true>; NodeDef: {{node FusedBatchNormV3}}. (Check whether your GraphDef-interpreting binary is up to date with your GraphDef-generating binary.).
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "detectvideo_counter.py", line 208, in <module>
app.run(main)
File "C:\Python37\lib\site-packages\absl\app.py", line 303, in run
_run_main(main, args)
File "C:\Python37\lib\site-packages\absl\app.py", line 251, in _run_main
sys.exit(main(argv))
File "detectvideo_counter.py", line 77, in main
saved_model_loaded = tf.saved_model.load(FLAGS.weights, tags=[tag_constants.SERVING])
File "C:\Python37\lib\site-packages\tensorflow_core\python\saved_model\load.py", line 528, in load
return load_internal(export_dir, tags)
File "C:\Python37\lib\site-packages\tensorflow_core\python\saved_model\load.py", line 552, in load_internal
export_dir)
File "C:\Python37\lib\site-packages\tensorflow_core\python\saved_model\load.py", line 114, in __init__
meta_graph.graph_def.library))
File "C:\Python37\lib\site-packages\tensorflow_core\python\saved_model\function_deserialization.py", line 312, in load_function_def_library
func_graph = function_def_lib.function_def_to_graph(copy)
File "C:\Python37\lib\site-packages\tensorflow_core\python\framework\function_def_to_graph.py", line 63, in function_def_to_graph
importer.import_graph_def_for_function(graph_def, name="")
File "C:\Python37\lib\site-packages\tensorflow_core\python\framework\importer.py", line 412, in import_graph_def_for_function
graph_def, validate_colocation_constraints=False, name=name)
File "C:\Python37\lib\site-packages\tensorflow_core\python\framework\importer.py", line 501, in _import_graph_def_internal
raise ValueError(str(e))
ValueError: NodeDef mentions attr 'exponential_avg_factor' not in Op<name=FusedBatchNormV3; signature=x:T, scale:U, offset:U, mean:U, variance:U -> y:T, batch_mean:U, batch_variance:U, reserve_space_1:U, reserve_space_2:U, reserve_space_3:U; attr=T:type,allowed=[DT_HALF, DT_BFLOAT16, DT_FLOAT]; attr=U:type,allowed=[DT_FLOAT]; attr=epsilon:float,default=0.0001; attr=data_format:string,default="NHWC",allowed=["NHWC", "NCHW"]; attr=is_training:bool,default=true>; NodeDef: {{node FusedBatchNormV3}}. (Check whether your GraphDef-interpreting binary is up to date with your GraphDef-generating binary.).
I tried to run this command in Colab:
! python detectvideo_counter.py --weights ./checkpoints/yolov4-416/ --size 608 --video {path_video} --score 0.9This is the result: